MOVLAB - Artigos de Revistas Internacionais com Arbitragem Científica

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    ColorShapeLinks: A board game AI competition for educators and students
    (Elsevier, 2021-02-23) Fachada, Nuno
    ColorShapeLinks is an AI board game competition framework specially designed for students and educators in videogame development, with openness and accessibility in mind. The competition is based on an arbitrarily-sized version of the Simplexity board game, the motto of which, “simple to learn, complex to master”, is curiously also applicable to AI agents. ColorShapeLinks offers graphical and text-based frontends and a completely open and documented development framework built using industry standard tools and following software engineering best practices. ColorShapeLinks is not only a competition, but both a game and a framework which educators and students can extend and use to host their own competitions. It has been successfully used for running internal competitions in AI classes, as well as for hosting an international AI competition at the IEEE Conference on Games.
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    Exploiting orientation information to improve range-based localization accuracy
    (IEEE Access, 2020) Tomic, Slavisa; Beko, Marko; Tuba, Milan
    This work addresses target localization problem in precarious surroundings where possibly no links are line of sight. It exploits the known architecture of available reference points to act as an irregular antenna array in order to estimate the azimuth angle between a reference point and a target, based on distance estimates withdrawn from integrated received signal strength (RSS) and time of arrival (TOA) observations. These ctitious azimuth angle observations are then used to linearize the measurement models, which triggers effortless derivation of a new estimator in a closed-form. It is shown here that, by using xed network geometry in which target orientation with respect to a line formed by a pair of anchors can be correctly estimated, the localization performance can be signi cantly enhanced. The new approach is validated through computer simulations, which corroborate our intuition of pro ting from inherent information within a network.
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    Special issue :localization in wireless sensor networks
    (MDPI Journal of Sensor and Actuator Networks, 2020) Tomic, Slavisa; Beko, Marko
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    Energy-based acoustic localization by improved elephant herding optimization
    (IEEE Access, 2020) Correia, Sérgio; Beko, Marko; Tomic, Slavisa; Cruz, Luís Alberto da Silva
    The present work proposes a new approach to address the energy based acoustic localization problem. The proposed approach represents an enhanced version of evolutionary optimization based on Elephant Herding Optimization (EHO), where two major contributions are introduced. Firstly, instead of random initialization of elephant population, we exploit particularities of the problem at hand to develop an intelligent initialization scheme. More precisely, distance estimates obtained at each reference point are used to determine the regions in which a source is most likely to be located at. Secondly, rather than letting elephants to simply wander around in their search for an update in the source location, we base their motion on a local search scheme which is found on a discrete gradient method. Such a methodology significantly accelerates the convergence of the proposed algorithm, and comes at a very low computational cost, since discretization allows us to avoid the actual gradient computations. Our simulation results show that the enhanced algorithm significantly outperforms the standard EHO method for low noise and matches its performance for high noise, in terms of localization accuracy. Moreover, they show that the proposed enhanced version requires significantly less number of iterations to converge.
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    A geometric approach for distributed multi-hop target localization in cooperative networks
    (IEEE Transactions on Vehicular Technology, 2020) Tomic, Slavisa; Beko, Marko
    This work addresses target localization problem in cooperative distributed sensor networks, in which all sensors are capable of measuring Received Signal Strength (RSS), but only some are appropriately equipped to measure Angle Of Arrival (AOA) of the received signal. A novel approach based on simple geometry and multi-hopping is proposed, which allows for natural conversion of the problem into a Generalized Trust Region Sub-Problem (GTRS). The proposed algorithm comprises three main steps, each of them with linear computational cost in the number of neighbors, making it suitable for real-time applications. Our simulation results validate the performance of the new algorithm, surpassing some significantly more complex ones, and almost achieving a lower bound set by an existing algorithm which uses some (unrealistic) assumptions in its favor.
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    Distributed localization with complemented RSS and AOA measurements : theory and methods
    (Applied Sciences, 2019) Tomic, Slavisa; Beko, Marko; Matos, Luís M. Camarinha de; Oliveira, Luís Bica
    Remarkable progress in radio frequency and micro-electro-mechanical systems integrated circuit design over the last two decades has enabled the use of wireless sensor networks with thousands of nodes. It is foreseen that the fifth generation of networks will provide significantly higher bandwidth and faster data rates with potential for interconnecting myriads of heterogeneous devices (sensors, agents, users, machines, and vehicles) into a single network (of nodes), under the notion of Internet of Things. The ability to accurately determine the physical location of each node (stationary or moving) will permit rapid development of new services and enhancement of the entire system. In outdoor environments, this could be achieved by employing global navigation satellite system (GNSS) which offers a worldwide service coverage with good accuracy. However, installing a GNSS receiver on each device in a network with thousands of nodes would be very expensive in addition to energy constraints. Besides, in indoor or obstructed environments (e.g., dense urban areas, forests, and canyons) the functionality of GNSS is limited to non-existing, and alternative methods have to be adopted. Many of the existing alternative solutions are centralized, meaning that there is a sink in the network that gathers all information and executes all required computations. This approach quickly becomes cumbersome as the number of nodes in the network grows, creating bottle-necks near the sink and high computational burden. Therefore, more effective approaches are needed. As such, this work presents a survey (from a signal processing perspective) of existing distributed solutions, amalgamating two radio measurements, received signal strength (RSS) and angle of arrival (AOA), which seem to have a promising partnership. The present article illustrates the theory and offers an overview of existing RSS-AOA distributed solutions, as well as their analysis from both localization accuracy and computational complexity points of view. Finally, the article identifies potential directions for future research.
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    The Role of the Non-Partisan Movements in Democracy. The Portuguese Case
    (Global Journals, 04/05/2020) Pinto, José Filipe
    - Since its birth in Greece, democracy has evolved mainly with regard to the role people or citizens must play in the system. That evolution explains not only the various modalities of democracy but also the formation of political parties and their change over time. There is no democracy without the parties, but the parties are not the owners of the democratic system, and this encourages the appearance of non-partisan movements that wish to be part of the power play. In Portugal, during Salazar’s dictatorship, political parties were forbidden. After returning to democracy, Portuguese law currently does not allow regional or local parties, as political parties need to act at the national level. However, the Constitution stipulated that non-partisan groups had the right to present lists to the lowest level of local power, the parish council. Despite the official constraint, these groups accepted the challenge, and their power and influence have increased since the first local election in 1976, and it was no wonder that, after the 1997 constitutional revision, the law had recognized them the right to apply for all the organs of the local power. Later, due to political dissents, some politicians decided to constitute non-partisan movements to run against the party that they had just abandoned. Nowadays, these groups rule over 17 of the 308 municipal councils, namely Porto, the second most important city in Portugal. Moreover, the nonpartisan movements are the third political force concerning local power, ruling over more than 400 parish councils. However, these groups cannot present lists to the central power, the National Assembly. This paper has a twofold aim. On the one hand, it analyses the evolution of the participation of non-partisan movements in the electoral acts, their influence in the political life in Portugal, their complaints against the electoral law, and their fight trying to change it. On the other hand, it sets out to explain the reaction of the parties towards the non-partisan groups and reflects on the modifications that these groups bring to democracy, adding a richness and depth to politics that has an impact on it.
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    Estimating Directional Data From Network Topology for Improving Tracking Performance
    (MDPI, 2019) Tomic, Slavisa; Beko, Marko; Dinis, Rui; Montezuma, Paulo
    This work proposes a novel approach for tracking a moving target in non-line-of-sight (NLOS) environments based on range estimates extracted from received signal strength (RSS) and time of arrival (TOA) measurements. By exploiting the known architecture of reference points to act as an improper antenna array and the range estimates, angle of arrival (AOA) of the signal emitted by the target is first estimated at each reference point. We then show how to take advantage of these angle estimates to convert the problem into a more convenient, polar space, where a linearization of the measurement models is easily achieved. The derived linear model serves as the main building block on top of which prior knowledge acquired during the movement of the target is incorporated by adapting a Kalman filter (KF). The performance of the proposed approach was assessed through computer simulations, which confirmed its effectiveness in combating the negative effect of NLOS bias and superiority in comparison with its naive counterpart, which does not take prior knowledge into consideration.
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    Algorithms for Estimating the Location of Remote Nodes Using Smartphones
    (IEEE, 2019) Pedro, Dario; Tomic, Slavisa; Bernardo, Luís; Beko, Marko; Oliveira, Rodolfo; Dinis, Rui; Pinto, Paulo; Amaral, Pedro
    Locating the position of a remote node on a wireless network is becoming more relevant, as we move forward in the Internet of things and in autonomous vehicles. This paper proposes a new system to implement the location of remote nodes. A new prototype Android application has been developed to collect real measurements and to study the performance of several smartphone's sensors and location algorithms, including an innovative one, based on the second order cone programming (SOCP) relaxation. The application collects theWiFi access points information and the terminal location. An internal odometry module developed for the prototype is used when Android's service is unavailable. This paper compares the performance of existing location estimators given in closed form, an existing SOCP one, and the new SOCP location estimator proposed, which has reduced complexity. An algorithm to merge measurements from non-identical terminals is also proposed. Cooperative and terminal stand-alone operations are compared, showing a higher performance for SOCP-based ones, that are capable of estimating the path loss exponent and the transmission power. The heterogeneous terminals were also used in the tests. Our results show that the accurate positioning of static remote entities can be achieved using a single smartphone. On the other hand, the accurate real-time positioning of the mobile terminal is provided when three or more scattered terminal nodes cooperate sharing the samples taken synchronously.
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    A Linear Estimator for Network Localization Using Integrated RSS and AOA Measurements
    (IEEE, 2019) Tomic, Slavisa; Beko, Marko; Tuba, Milan
    This letter addresses the problem of simultaneous localization of multiple targets in three-dimensional cooperative wireless sensor networks. To this end, integrated received signal strength and angle of arrival measurements are employed. By exploiting the convenient nature of spherical representation of the considered problem, the measurement models are linearized and a sub-optimal estimator is formulated. Unlike the maximum likelihood estimator, which is highly non-convex and difficult to tackle directly, the derived estimator is quadratic and has a closed-form solution. Its computational complexity is linear in the number of connections and its accuracy surpasses the accuracy of existing ones in all considered scenarios.
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    Target Localization via Integrated and Segregated Ranging Based on RSS and TOA Measurements
    (MDPI, 2019) Tomic, Slavisa; Beko, Marko
    This work addresses the problem of target localization in adverse non-line-of-sight (NLOS) environments by using received signal strength (RSS) and time of arrival (TOA) measurements. It is inspired by a recently published work in which authors discuss about a critical distance below and above which employing combined RSS-TOA measurements is inferior to employing RSS-only and TOA-only measurements, respectively. Here, we revise state-of-the-art estimators for the considered target localization problem and study their performance against their counterparts that employ each individual measurement exclusively. It is shown that the hybrid approach is not the best one by default. Thus, we propose a simple heuristic approach to choose the best measurement for each link, and we show that it can enhance the performance of an estimator. The new approach implicitly relies on the concept of the critical distance, but does not assume certain link parameters as given. Our simulations corroborate with findings available in the literature for line-of-sight (LOS) to a certain extent, but they indicate that more work is required for NLOS environments. Moreover, they show that the heuristic approach works well, matching or even improving the performance of the best fixed choice in all considered scenarios.
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    A Robust NLOS Bias Mitigation Technique for RSS-TOA-Based Target Localization
    (IEEE, 2019) Tomic, Slavisa; Beko, Marko
    This letter proposes a novel robust mitigation technique to address the problem of target localization in adverse nonline- of-sight (NLOS) environments. The proposed scheme is based on combined received signal strength and time of arrival measurements. Influence of NLOS biases is mitigated by treating them as nuisance parameters through a robust approach. Due to a high degree of difficulty of the considered problem, it is converted into a generalized trust region sub-problem by applying certain approximations, and solved efficiently by merely a bisection procedure. Numerical results corroborate the effectiveness of the proposed approach, rendering it the most accurate one in all considered scenarios.
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    Target Localization in NLOS Environments Using RSS and TOA Measurements
    (IEEE, 2018) Tomic, Slavisa; Beko, Marko; Tuba, Milan; Correia, Victor M. Franco
    This letter addresses the problem of target localization in adverse non-line-of-sight environments. By utilizing integrated received signal strength and time of arrival measurements, a novel alternating algorithm is proposed. The new algorithm is derived by converting the original nonconvex problem into a generalized trust region sub-problem framework, which can be solved exactly by just a bisection procedure. Therefore, the proposed algorithm is very light in terms of computational cost, and its excellent estimation accuracy is validated through computer simulations.
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    Elephant Herding Optimization for Energy-Based Localization
    (MDPI, 2018) Correia, Sérgio; Beko, Marko; Cruz, Luís Alberto da Silva; Tomic, Slavisa
    This work addresses the energy-based source localization problem in wireless sensors networks. Instead of circumventing the maximum likelihood (ML) problem by applying convex relaxations and approximations, we approach it directly by the use of metaheuristics. To the best of our knowledge, this is the first time that metaheuristics are applied to this type of problem. More specifically, an elephant herding optimization (EHO) algorithm is applied. Through extensive simulations, the key parameters of the EHO algorithm are optimized such that they match the energy decay model between two sensor nodes. A detailed analysis of the computational complexity is presented, as well as a performance comparison between the proposed algorithm and existing non-metaheuristic ones. Simulation results show that the new approach significantly outperforms existing solutions in noisy environments, encouraging further improvement and testing of metaheuristic methods.
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    On Target Localization Using Combined RSS and AoA Measurements
    (MDPI, 2018) Tomic, Slavisa; Beko, Marko; Dinis, Rui; Bernardo, Luís
    This work revises existing solutions for a problem of target localization in wireless sensor networks (WSNs), utilizing integrated measurements, namely received signal strength (RSS) and angle of arrival (AoA). The problem of RSS/AoA-based target localization became very popular in the research community recently, owing to its great applicability potential and relatively low implementation cost. Therefore, here, a comprehensive study of the state-of-the-art (SoA) solutions and their detailed analysis is presented. The beginning of this work starts by considering the SoA approaches based on convex relaxation techniques (more computationally complex in general), and it goes through other (less computationally complex) approaches, as well, such as the ones based on the generalized trust region sub-problems framework and linear least squares. Furthermore, a detailed analysis of the computational complexity of each solution is reviewed. Furthermore, an extensive set of simulation results is presented. Finally, the main conclusions are summarized, and a set of future aspects and trends that might be interesting for future research in this area is identified.
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    Exact Robust Solution to TW-ToA-Based Target Localization Problem With Clock Imperfections
    (IEEE, 2018) Tomic, Slavisa; Beko, Marko
    This letter addresses the problem of target localization based on two-way time of arrival (TW-ToA) measurements with clock imperfections. In addition to the target location, the turn-around times and clock skews are considered unknown. Since an optimal estimator for this problem cannot be tackled directly, we approximate it by a suboptimal, robust one, formulated as a generalized trust region subproblem. Even though nonconvex in general, exact solution of the derived estimator can be obtained by just a bisection procedure. Simulation results validate the effectiveness of the proposed technique, matching the performance of the state of the art with significantly lower computational complexity.
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    A bisection-based approach for exact target localization in NLOS environments
    (Elsevier, 2017) Tomic, Slavisa; Beko, Marko
    This work addresses the range-based target localization problem in adverse non-line-of-sight (NLOS) en- vironments. We start by deriving the maximum likelihood (ML) estimator from the measurement model, since it is asymptotically efficient. However, this estimator is highly non-convex and difficult to solve di- rectly. Hence, we convert the localization problem into a generalized trust region sub-problem (GTRS) framework. Although still non-convex in general, the derived estimator is strictly decreasing over a read- ily obtained interval, and thus, can be solved exactly by a bisection procedure. In huge contrast to exist- ing algorithms, which either require the knowledge about the magnitude of the NLOS bias or to a priori distinguish between line-of-sight (LOS) and NLOS links, the new one does not require such prerequi- sites. Also, the computational complexity of the proposed algorithm is linear in the number of reference nodes, unlike the majority of existing ones. Our simulation results show that the new algorithm possesses a steady NLOS bias mitigation capacity and that it represents an excellent alternative in the sense of the trade offbetween accuracy and complexity. To be more specific, it not only matches the performance of existing methods (majority of which significantly more computationally complex) but outperforms them in general. Moreover, the performance of the proposed algorithm is validated through real-indoor exper- imental data.
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    Bayesian methodology for target tracking using combined RSS and AoA measurements
    (Elsevier, 2017) Tomic, Slavisa; Beko, Marko; Dinis, Rui; Tuba, Milan; Bacanin, Nebojsa
    This work addresses the target tracking problem based on received signal strength (RSS) and angle of arrival (AoA) measurements. The Bayesian methodology, which integrates the information given by observations with prior knowledge extracted from target motion model in order to enhance the estimation accuracy was employed. First, by converting the considered highly non-linear measurement model into a linear one, i.e., a novel linearization technique of the measurement model is proposed. The derived model is then merged with the prior knowledge, and a novel maximum a posteriori (MAP) estimator whose solution is given in closed-form is proposed. It is also shown that the Kalman filter (KF) can be directly applied on top of the linearized observation model, which results in a proposal of a novel KF algorithm. Furthermore, to the best of authors’ knowledge, this paper premierly presents the application of the extended KF (EKF) and the unscented KF (UKF) to the considered tracking problem, by applying first-order linearization technique to the original non-linear model, and by applying the unscented transformation to carefully selected sample points, respectively. Finally, importance weights are computed for a large number of randomly selected sample points to render a well-known particle filter (PF) solution. Simulation results show that the proposed algorithms perform better than a naive one which uses only information from observations. They also confirm the effectiveness of the proposed linearization technique in comparison with the existing one, reducing the estimation error for about 25%.
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    Target Tracking with Sensor Navigation Using Coupled RSS and AoA Measurements
    (MDPI, 2017) Tomic, Slavisa; Beko, Marko; Dinis, Rui; Gomes, João Pedro
    This work addresses the problem of tracking a signal-emitting mobile target in wireless sensor networks (WSNs) with navigated mobile sensors. The sensors are properly equipped to acquire received signal strength (RSS) and angle of arrival (AoA) measurements from the received signal, while the target transmit power is assumed not known. We start by showing how to linearize the highly non-linear measurement model. Then, by employing a Bayesian approach, we combine the linearized observation model with prior knowledge extracted from the state transition model. Based on the maximum a posteriori (MAP) principle and the Kalman filtering (KF) framework, we propose new MAP and KF algorithms, respectively. We also propose a simple and efficient mobile sensor navigation procedure, which allows us to further enhance the estimation accuracy of our algorithms with a reduced number of sensors. Model flaws, which result in imperfect knowledge about the path loss exponent (PLE) and the true mobile sensors’ locations, are taken into consideration. We have carried out an extensive simulation study, and our results confirm the superiority of the proposed algorithms, as well as the effectiveness of the proposed navigation routine.
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    The Siren Song of Populism
    (Global Journals, 2019-03) Pinto, José Filipe
    Populism is not a fad or an epiphenomenon. As the election results prove, populism is increasing almost all over the world, and populists rule the four most crowed democracies. Populist parties are gaining ground in the majority of the EU countries and in the two latest American presidential elections two populists – Donald Trump and Bolsonaro – achieved the power stage of the USA and Brazil. In the European Union, after a long period, while populist parties assumed an anti-system position, most of the populists changed their strategy trying to reach the power, and they are already the third political force. This increase has been constant. However, the economic recession and the large flow of refugees and immigrants were at the roof of the most recent rise. The essay analyses the populist parties’ strategic change and the reaction of the mainstream parties. It also explains that right-wing populism is using the nationalist rhetoric and some policies of social democracy into the service of nationalism, and it is increasing faster than the left-wing one. Moreover, the essay shows that populist governments stay in power longer than non-populists do. Finally, it proves that the populist discourse works as a new siren song because populist leaders say what the citizens are keen to hear